There is often significant heterogeneity present in the context of systems engineering problems. This heterogeneity can limit the effectiveness of policies and models that are designed to operate at a coarse, population level when the actual point of intervention is at the level of the specific and varying subgroups or individuals constituting the population. Thus, methods of model personalization may be required to achieve desired outcomes. In this dissertation, we propose a means of rapid, online model personalization of decision rules based on statistical learning models, GMAdapt, which is informed by the context of decision support systems for the management of type 1 diabetes. To evaluate the effectiveness of this procedure, we performed experiments using both numerical simulations and retrospective data analysis based on real-world clinical trials conducted at the UVa Center for Diabetes Technology. In addition to the adaptation procedure itself, we present a simulation based methodology for deconfounding data to address the issue of intervention generated label noise. This method is evaluated in silico using the UVa/Padova type 1 diabetes simulator and compared against some alternative methodologies for creating end-to-end systems capable of adaptively learning personalized decision rules in spite of system generated interventions and resulting label noise.
Using Kotter's Eight-Stage Process of Leading Change as a framework, this chapter describes the motivations for, process of, and outcomes from an effort at the University of Virginia Library to analyze and update the multifaceted digital production workflow.
In the scattering process off a nuclear or nucleon target, the Gerasimov-Drell-Hearn (GDH) sum rule for real photons ($Q^2$=0 where $Q^2\equiv -q^2$ with $q$ the photon's 4-momentum) relates static properties of the target particle's ground state to dynamic properties of all its excited states. On the other side of the $Q^2$ spectrum, the Bjorken sum rule holds in the Bjorken limit $Q^2 \rightarrow \infty$. Bjorken sum rule relates the final structure functions of the proton and neutron to the nucleon axial coupling constant in weak decay. These two sum rules belong to domains where calculations are achievable but use different degrees of freedom: hadronic degrees of freedom at low $Q^2$ versus partonic degrees of freedom at intermediate $Q^2$. Meanwhile, different methods have been used to connect the two sum rules at finite $Q^2$ values: Chiral Perturbation Theory is used to expand the GDH sum rule while Operator Product Expansion is used to expand the Bjorken sum rule. In recent decades, improvements in polarized beam and polarized target techniques have made it possible to test theoretical predictions in the intermediate $Q^2$ region. During the Jefferson Lab (JLab) Hall A E97110 experiment, a precise measurement of polarized cross sections was performed at $0.02
What are we to make of Donald Trump? Since 2015, Trump has dominated American politics and rebuilt a major political party in his own image. Despite being initially dismissed as a joke candidate whose campaign for president was, at best, a symbolic crusade against the establishment on issues such as trade, immigration, and foreign policy, and at worst, nothing more than a public relations stunt, Trump went on to capture the Republican nomination and then shocked the world by defeating Hillary Clinton in November, 2016. This dissertation attempts to make sense of this phenomenon by examining Trump’s political philosophies and actions, both as a candidate and as president, from numerous theoretical perspectives, particularly as they relate to trade policy. The first section of the dissertation puts Trump in the historical context of Republican political thought by documenting the linear tradition of Trump’s trade positions all the way back to the Founding, particularly through the tradition of Hamiltonianism. Next, the dissertation looks at the election of 2016, with particular focus on the Republican primaries, in order to understand how and why Trump won the nomination and, eventually, the Oval Office. The last part of the dissertation looks at how his beliefs on trade have guided his actions on trade as president, with China and NAFTA as the main case studies. In the end, the dissertation shows that Trump tapped into a forgotten and dormant, but not extinct, base of protectionist Republican voters in order to win the Oval Office, destroyed an illusory Republican Party consensus on trade, demonstrated that ideological values are hardly more than meaningless heuristics, and realigned American politics in ways that may be beneficial to the Republican Party in the short-term, but pose long-term dangers. As such, it adds to the exponentially-growing literature on the rise of Donald Trump and his presidency, particularly with respect to Trump’s trade narratives.
The use of standardized anthropomorphic test devices and test conditions prevent current vehicle development and safety assessments from capturing the breadth of variability inherent in real-world occupant responses. The central idea of this dissertation is that human body models used in simulations with a diverse range of real-world impact scenarios can represent population variability and may be the key to overcome the limitations of current vehicle assessment and development methodologies. In this approach, a series of response surfaces are created that contain information about the occupant responses as a function of different input variables. Subsequently, these surfaces, in conjunction with real-world distributions of the population and impact conditions, can be used to identify populations at risk, to illustrate injurious impact scenarios, and to inform prioritization of countermeasure and design actions. This dissertation develops a methodology to assess occupant response that accounts for sources of intrinsic (human-related) and extrinsic (non-human-related) variability, including uncertainty in the FE parameters. Although inherently generic in nature, this methodology was applied to a far-side crash scenario in order to provide an illustrative example. For the far-side application, lateral head excursion and thoracic injury were identified as the target occupant responses, while change in vehicle velocity, impact direction and seatbelt load limiter were the extrinsic factors explored. The intrinsic factors were occupant height, weight and waist circumference and were explored by morphing the simplified GHBMC human body model. WorldSID tests were used in order to validate and estimate the parameter uncertainty in the vehicle FE model. Five regression techniques, namely, linear regression, logistic regression, LASSO linear and logistic regression, and Neural Networks (NN), were used for the generation of the response surfaces. The regression models were sequentially trained to represent the maximum lateral head excursion and the probability of 3+ fractured ribs using a total of 405 FE simulation results. The performance of these regression techniques was assessed based on their ability to predict out-of-sample datapoints. The NN showed equal or improved performance with respect to the other regression techniques. Based on far-side input conditions derived from US field data, Monte-Carlo simulations used the head excursion and rib fracture response surfaces to calculate the probability of head-to-intruding-door impacts and cases with 3+ fractured ribs. In addition, the Monte-Carlo analysis predicted head contact and rib fracture reductions subsequent to design changes in the restraint configuration. This analysis indicated that the vehicle used in this study would lead to a range of 667 to 2,448 head-to-intruding-door impacts and a range of 2,893 to 3,783 cases of 3+ fractured ribs, depending on the seatbelt load limiter. In the US field data, the expected number of cases with 3+ fractured ribs was 3,958. The far-side assessment illustrates how the methodology incorporates the intrinsic and extrinsic variability, generates response surfaces that characterize the effects of the variability, and ultimately permits vehicle design considerations and injury predictions appropriate for real-world field conditions.
Creating interventions to avoid adverse events is an ongoing topic in numerous settings and thus it is often important to answer questions such as which treatments can be applied to avoid outcomes such as death or stunted growth. One may hope to answer these queries through the use of variable importance measures and through modeling the growth and development of individuals. Variable importance is an up and coming aspect of statistics that ranks variables in terms of some measure of importance which is often applied without the notion of either the exact meaning or how it can be compared with other regression or classification methods. Thus, characterizing standard variable importance measures could go a long way in the applicability and practicality of these ideas. In addition, confidence intervals and a lower threshold of importance was created and explored in order to advance the understanding and interpretability of such measures and methods. Simulations were conducted to show the behavior of such metrics with theoretical results stemming from a simple setting. In a specific population of Bangladeshi children from the PROVIDE study, growth models were explored where previous models have not correctly described these children's heights over the first two years of time, especially considering the plethora of covariates (900+). Developmental outcomes from 2 to 5 years of age were additionally modeled and explored. Throughout this research, the variable importance is described and explored in diverse manners while the children's heights and development is explained through various inclusive models.
This dissertation explores students’ access to high-quality information and advisors to help them advance through the K-12 education system and into the postsecondary system. Financial aid policies are an example of one type of high-resource, high-intensity intervention to address income gaps in college-going. However, there are several other potential policy interventions that address the non-pecuniary resources students need to navigate the education system, and there are several leverage points earlier in students’ education trajectory that merit intervention well before students make the decision about whether and where to apply to college.
This dissertation introduces various cultural reponses to the 2008 social and financial crisis in Spain. In particular, the project identifies key outcomes of the actual crash and demonstrates how cultural works have depicted the catastrophe. My work underscores other functions of these artistic manifestations ranging from providing catharsis to encouraging protest and activism. The dissertation explores multiple cultural phenomena including novel, theatre, film, television, comic, and street performance. It offers the first critical analysis of many of these texts.
In the Introduction, I highlight the historical background leading up to the 2008 recession and discuss the consequences of the disaster. I point to culture as a means to move beyond numbers and figures in order to illuminate the human suffering and response to the crash. In this chapter, I offer an overview of previous scholarship on the crisis and cultural production and point to the need for an ongoing conversation. I underscore that my dissertation fills a void in the study of these phenomena by providing an analysis of multiple mediums.
Chapter One discusses the first thematic response to the crisis: suffering and marginality. It demonstrates the human dimension of the disaster through analyses of the play Iphigenia en Vallecas, Isaac Rosa’s comic, Aquí vivió, and Icíar Bollaín’s film, El olivo. Chapter Two centers on the mass Spanish emigration that occurred after the advent of the crisis. The chapter provides an overview of recent Spanish migration patterns and how these are represented through culture. Venirse arriba (2014), by Borja Cobeaga and Diego San José, Blitz (2015), by David Trueba, the film Perdiendo el norte (2015), directed by Nacho Velilla, as well as the television series, Buscando el norte (2016), created by Nacho Velilla, Oriol Capel, David Olivas, and Antonio Sánchez serve as case studies to represent this phenomenon. Chapter Three examines how culture can serve as a mode of protest through an analysis of María Folguera’s novel, Los primeros días de Pompeya (2016), Alberto San Juan’s play, Masacre: Una historia del capitalismo español (2017), and the Flo6x8 flamenco flash-mob group.
In the past two decades, contemporary nature poetry has increasingly abandoned traditional representations of nature, instead privileging the complex and often messy entanglements that characterize our climate change era. Jorie Graham’s 2008 poetry collection, Sea Change, stands out among this group for its depiction of the material and affective relations between human and nonhuman life in a time of profound ecological crisis. This thesis argues that Sea Change draws on new materialist concepts to articulate a posthuman or more-than-human subjectivity and ethics for the Anthropocene, a relational mode of being oriented towards principles of non-mastery. Departing from more radical formulations of ecological poetry that would attempt to eliminate the human subject and voice altogether, Graham’s work balances her concern for the “in- / dispensable plankton” with the lyric intimacy and minutiae of human life. In doing so, Sea Change enlivens the theoretical debates surrounding subjectivity and ethics in the Anthropocene, helping us to imagine how we, Graham’s readers, might begin to exhibit these selves in our everyday life.
The collective action of microbes that colonize humans, known as their microbiota, has emerged as a major force influencing health and disease. Appreciation for this influence has grown exponentially in recent years thanks to advances in high-throughput sequencing technologies that were coupled with key concepts in microbial ecology and evolution linking sequence to phylogeny. Although studies utilizing these technologies, and the analytic methods also required to enable them, have greatly advanced our understanding of the potential impact of the microbiota on human health, we still lack systematic methods for interrogating the mechanisms responsible for the numerous associations we have identified. In this dissertation, I present my work which accelerates our ability to develop actionable hypotheses from associations observed in studies of the microbiota. This work is divided into data-driven approaches for inferring metabolic mechanisms governing interspecies interactions (Chapter 2), and model-driven approaches for improving our understanding of metabolism for gut microbes (Chapters 3 and 4). In Chapter 2, I developed a method that establishes expected metabolic behavior within microbial communities based on the assumption of constant metabolite yield between mono- and co-culture conditions. Using this method, I identified global improvements in the efficiency of biomass production that occur in co-cultures in which a species experienced a growth benefit, and show that the method can be used to interrogate complex interspecies interactions such as cross feeding. In Chapters 3 and 4, I developed software and method for building and analyzing ensembles of genome-scale metabolic network reconstructions. I used these tools to address a key challenge in systems biology: how should curation of large mechanistic models be prioritized? I developed an ensemble generation, simulation, and analysis framework that identifies key curation targets that maximally reduce simulation uncertainty, thereby establishing the relative value of curating each portion of a metabolic network. In sum, the work in this dissertation represents advances in our ability to interrogate interactions between gut microbes as well as our ability to efficiently construct predictive models of metabolism for individual species.